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IEEE CIS Newsletter, Issue 117, October 2022

Celebrate IEEE Day with CIS Distingushed Lecturer Professor Hussein Abbass

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From Machine Learning to Machine Education
Monday, 10 October 2022 
7:00 AM - 8:00 AM EDT / 10:00 PM - 11:00 PM AEDT

IEEE Day is an annual event that celebrates the first time in history when engineers worldwide gathered to share their technical ideas in 1884. One of the IEEE Day's objectives is to show the ways IEEE members, in local communities, join together to collaborate on ideas that leverage technology for a better tomorrow. Celebrate IEEE Day with CIS and register for our live webinar: From Machine Learning to Machine Education with Professor Hussein Abbass, CIS Distingushed Lecturer. Machine learning focuses on algorithms and architectures to enable machines to improve performance from experience. Machine teaching focuses on the design of the experience required by a machine to learn. Machine education is concerned with pedagogical design of the processes to empower an AI-enabled system with the experiences and learning processes to design ethical, responsible, and safe smart autonomous systems. This talk will present on machine education and the pedagogical design of smart autonomous systems. Examples will be provided using neural-network-based machine education case studies.

Hussein Abbass is a Professor at the School of Engineering and Information Technology at University of New South Wales, Canberra, Australia. He is the Founding Editor-in-Chief for the IEEE Transactions on Artificial Intelligence.


Call for Associate Editors for the IEEE Transactions on Artificial Intelligence


Deadline for applying: 3 December 2022

Each year, the IEEE Transactions on Artificial Intelligence (IEEE TAI) invites new Associate Editors (AEs) to join its editorial board due to completion of the term of some existing AEs, retention of some AEs, or an increased load on existing AEs in some areas of AI.

The journal encourages diversity and people from industry and/or government organisations who possess a strong track record in AI to apply.

Areas of particular interest include: Adversarial Learning, Bayesian Networks, Distributed Artificial Intelligence, Ethics of Artificial Intelligence, Fairness and Accountability of Artificial Intelligence, Human-AI Interaction / Teaming, Hyper and Meta Graphs, Knowledge-based Systems, Knowledge Graphs, Machine Learning for Image Processing, Machine Learning for Video Processing, Mathematical Logic, Multi-armed Bandit, Symbolic and non-Symbolic Knowledge Representation, Symbolic and non-Symbolic Natural Language Processing, Ontology, Probabilistic Reasoning, Reinforcement Learning, Sentiment Analysis, Swarm Robotics, Symbolic Reasoning, Trust in Artificial Intelligence, and Unmanned Systems.

Candidates interested in applying to join IEEE TAI’s editorial board must apply by filling the form here.

Member Activities

Live Webinar with Professor Anna Wilbik

The Explainability Challenge in Descriptive Analytics: Do We Understand the Data?

Wednesday, 16 November 2022
8:00 AM - 9:00 AM EST

Nowadays, ever more data is collected, for instance in the healthcare domain. The amount of patients’ data has doubled in the previous two years. This exponential growth creates a data flood that is hard to handle by decision makers. In many domains, humans are collaborating with machines for decision making purposes to cope with the resulting data complexity and size. This collaboration can be realized through machine learning, visual analytics, or online analytical processing, where a machine is just a tool – but often used to take important decisions. Read more

Anna Wilbik is currently Professor in Data Fusion and Intelligent Interaction in the Department of Advanced Computing Sciences of Maastricht University, in the Netherlands. Currently she is also a chair of The Fuzzy Systems Technical Committee (FSTC) within IEEE CIS. 

Research Frontier

Comparing the Performance of Evolutionary Algorithms for Sparse Multi-Objective Optimization via a Comprehensive Indicator

Many real-world multi-objective optimization problems (MOPs) are characterized by a large number of decision variables, where the decision variables are mostly set to zero in the Pareto optimal solutions. Although some multi-objective evolutionary algorithms (MOEAs) have been tailored for large-scale MOPs in recent years, most of them do not consider the sparse nature of Pareto optimal solutions, and their effectiveness to sparse MOPs has not been investigated. Therefore, this work aims to compare the performance of MOEAs on sparse MOPs by suggesting a comprehensive performance indicator. Read More

IEEE Computational Intelligence Magazine, August 2022


Generating Black-Box Adversarial Examples in Sparse Domain

Applications of machine learning (ML) models and convolutional neural networks (CNNs) have been rapidly increased. Although state-of-the-art CNNs provide high accuracy in many applications, recent investigations show that such networks are highly vulnerable to adversarial attacks. The black-box adversarial attack is one type of attack that the attacker does not have any knowledge about the model or the training dataset, but it has some input data set and their labels. In this paper, we propose a novel approach to generate a black-box attack in sparse domain whereas the most important information of an image can be observed. Read More

Transactions on Emerging Topics in Computational Intelligence, August 2022


A Gradient-Guided Evolutionary Approach to Training Deep Neural Networks

six layers of neural networks illustrationIt has been widely recognized that the efficient training of neural networks (NNs) is crucial to classification performance. While a series of gradient-based approaches have been extensively developed, they are criticized for the ease of trapping into local optima and sensitivity to hyperparameters. Due to the high robustness and wide applicability, evolutionary algorithms (EAs) have been regarded as a promising alternative for training NNs in recent years. However, EAs suffer from the curse of dimensionality and are inefficient in training deep NNs (DNNs). By inheriting the advantages of both the gradient-based approaches and EAs, this article proposes a gradient-guided evolutionary approach to train DNNs. Read More

IEEE Transactions on Neural Networks and Learning Systems, September 2022


Region-Focused Memetic Algorithms With Smart Initialization for Real-World Large-Scale Waste Collection Problems

recycling truck in green illustrationMemetic algorithm (MA) is widely applied to optimize routing problems as it provides one way to combine local search with global search. However, the local search in MA needs to be carefully designed according to the problem’s characteristics. In this article, we consider a real-world large-scale waste collection problem with multiple depots, multiple disposal facilities, multiple trips, and working time constraints. Vehicles with a limited capacity and working time can start from different depots, collect waste at different sites, and make multiple trips to different disposal facilities to empty the waste and return to its origin. While the existing work considered problems with multiple trips and time constraints, none have tackled problems with multiple depots, multiple disposal facilities, multiple trips, as well as working time constraints. Read More

IEEE Transactions on Evolutionary Computation, August 2022


Danesh: Interactive Tools for Understanding Procedural Content Generators

hand touching buttons on a screenIn order to advance the field of procedural content generation, and transfer knowledge from academic research to everyday use, we need to develop tools that make generative systems easier to understand and control. In this article, we introduce Danesh, a plugin to the unity game development environment, which helps provide a suite of tools that provide automation or analysis of different aspects of procedural generators. We describe here the features of Danesh, including automatic analysis of generated content, the visualization of generative spaces, automatic parameter discovery, and interface smoothing. We also provide reflections on our development of the tool so far. Read More

IEEE Transactions on Games, September 2022


Action Command Encoding for Surrogate-Assisted Neural Architecture Search

With the development of neural architecture search, the performance of deep neural networks has been considerably enhanced with less human expertise. While the existing work mainly focuses on the development of optimizers, the design of encoding scheme is still in its infancy. This article thus proposes a novel encoding scheme for neural architecture search, termed action command encoding (ACEncoding). Inspired by the gene expression process, ACEncoding defines several action commands to indicate the addition and clone of layers, connections, and local modules, where an architecture grows from empty according to multiple action commands. ACEncoding provides a compact and rich search space that can be explored by various optimizers efficiently. Read More

IEEE Transactions on Cognitive and Developmental Systems, August 2022

Educational Activities

IEEE CIS Summer School 2022 at NIT Arunachal Pradesh


The main objective of the summer school is to understand the importance and relevance of emerging research trends in Computational Intelligence (CI) techniques among the community of young researchers and to acquire transversal skills in the wide range of biomedical data and imaging applications development. This summer school is not only offering the lectures but also providing a wonderful opportunity for young researchers and students to participate in interactive session for building their confidence and knowledge. Several well-known and renowned speakers of the relevant fields will exchange their learning, research ideas and hands-on training among the summer school participants that will be helpful in the future of research direction. The attractive feature of this summer school is to contribute knowledge by following the recent advancement of computational intelligence for biomedical imaging and data with different application domains.


Dates: 7-11 November 2022

Venue: NIT Arunachal Pradesh, India Theme: Emerging Research Trends in Computational Intelligence Techniques to address Challenges in Biomedical Data and Imaging (hybrid mode).


Call for the 2022 Competition on Solar Generation Forecasting


Benchmarking of artificial intelligence methods for solar generation forecasting to address the increasing importance of energy resources forecasting in current and future power and energy systems.

Deadline: 31 October 2022

Organizers: Tiago Pinto, Zita Vale, and Luis Gomes (Polytechnic of Porto, Portugal) Supported by IEEE CIS Task Force on Computational Intelligence in the Energy Domain.

Competition Website:

Scope and Topics: Energy resources forecasting is increasingly important in current and future power and energy systems. Due to the high uncertainty of generation based on renewable energy sources, which results from their dependence on weather conditions, such as wind speed or solar intensity, the need to develop suitable solutions to deal with such variability increases considerably. This competition fosters the benchmarking of artificial intelligence methods for solar generation forecasting.

Submission Instructions: The forecasts for each hour of the 7 days must be submitted in XLS format after submission, the teams with the best results will be requested to present their solution in a remote session with the jury.

Journal Special Issues
Due to the outbreak of the COVID-19 pandemic, dates and details of CIS sponsored conferences should be monitored closely.

The situation is changing very quickly. Please consult the conference web pages frequently to obtain the latest information.

You can find the most recent announcements and updates from all of our Society’s conferences and events at IEEE CIS COVID-19 Notice page as our organizers make decisions.

By Marley Vellasco, Pontifícia Universidade Católica do Rio de Janeiro, Brazil
Leandro Minku, University of Birmingham, UK

* Denotes a CIS-Sponsored Conference
∆ Denotes a CIS Technical Co-Sponsored Conference

∆ 2022 First International Conference on Cyber-energy Systems and Intelligent Energy (ICCSIE 2022)
12-13 October 2022
Place: Beijing, China
General Chairs: Huaguang Zhang and Derong Liu
Website: TBA

∆ The 2nd International Conference on AI-ML Systems (AIML 2022)
12-15 October 2022
Place: Bangalore, India
General chairs: Ralf Herbrich, Dan Roth and Rajeev Rastogi
Submission: 5 July 2022

* 2022 IEEE International Conference on Data Science and Advanced Analytics (IEEE DSAA 2022)
13-16 October 2022
Place: Shenzhen, China
General Chairs: Joshua Huang, Gary Yen and Karoli Skala

∆ International Conference on Intelligent Systems and Computational Intelligence (ICISCI 2022)
15-17 October 2022
Place: Changsha, China
General Chairs: Tingwen Huang and Chunhua Yang

∆ 4th International Conference on Process Mining (ICPM 2022)
23-28 October 2022
Place: Bolzano, Italy
General Chair: Marco Montali

∆ 2022 Asian Conference on Artificial Intelligence Technology (ACAIT 2022)
28-30 October 2022
Place: Changzhou, China
General Co-Chairs: Qionghai Dai, Cesare Alippi and Jong-Hwan Kim

∆ The 2022 International Conference on Behavioural and Social Computing (BESC 2022)
29-31 October 2022
Place: Matsuyama, Japan
General Chair: Prof. Shiro Uesugi

∆ The 17th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP 2022)
3-4 November 2022
Place: Virtual
General Co-Chairs: Phivos Mylonas and Katia-Lida Kermanidou

* IEEE Latin-America Conference on Computational Intelligence (IEEE LA-CCI 2022)
23-25 November 2022
Place: Montevideo, Urugay
General Chair: Martin Pedemonte and Hector Cancela

* 2022 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2022)
4-7 December 2022
Place: Singapore
General Chairs: Ah-Hwee Tan, Dipti Srinivasan and Chunyan Miao

* 2022 IEEE Smart World Conference (IEEE SWC 2022)
16-18 December 2022
Place: Haikou, China
General Chair: Laurence T. Yang

∆ 12th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2023)
22-24 February 2023
Place: Lisbon, Portugal
General Chair: Ana Fred

∆ 15th International Conference on Agents and Artificial Intelligence (ICAART 2023)
22-24 February 2023
Place: Lisbon, Portugal
General Chair: Jaap van den Herik

∆ 10th International Conference on Signal Processing and Integrated Networks (SPIN 2023)
23-24 March 2023
Delhi, India
General Chair: Manoj Kumar Pandey

* 2023 IEEE Conference on Artificial Intelligence (IEEE CAI 2023)
7-8 June 2023
Place: Santa Clara Valley, USA
General Chairs: Gary Fogel and Piero Bonissone

* IEEE Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (IEEE CIVEMSA 2023)
12-14 June 2023
Place: Tunis, Tunisia
General Chair: Adel M. Alimi

∆ 2023 International Joint Conference on Neural Networks (IJCNN 2023)
18-23 June 2023
Place: Gold Coast, Australia
General Chairs: Brijesh Verma and Nik Kasabov

* 2023 IEEE Swiss Conference on Data Science (IEEE SDS 2023)
22-23 June 2023
Place: Zurich, Switzerland
General Chair: Melanie Geiger
Website: TBA

* 2023 IEEE Congress on Evolutionary Computation (IEEE CEC 2023)
2-5 July 2023
Place: Chicago, USA
General Chair: Gui DeSouza

* 2023 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2023)
13-17 August 2023
Place: Incheon, Korea
General Co-Chairs: Frank Chung-Hoon Rhee and Byung-Jae Choi

* 2023 IEEE Conference on Games (IEEE CoG 2023)
21-24 August 2023
Place: Boston, USA
General chairs: Casper Harteveld and Jialin Liu
Website: TBA

* 2023 IEEE Smart World Congress (IEEE SWC 2023)
25-28 August 2023
Place: Portsmouth, UK
General chairs: Hui Yu and Man Lin
Website: TBA

* IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB 2023)
29-31 August 2023
Place: Eindhoven, Netherlands
General Chair: Marco S. Nobile

* 2022 IEEE International Conference on Data Science and Advanced Analytics (IEEE DSAA 2023)
2-6 October 2023
Place: Thessaloniki, Greece
General Chair: Yannis Manolopoulos
Website: TBA

* 2023 IEEE International Conference on Development and Learning (ICDL-EpiRob 2023)
9-11 November 2023
Place: Macau, China
General Chair: Zhijun Li
Website: TBA

* 2023 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2023)
6-8 December 2023
Place: Mexico City, Mexico
General Chair: Wen Yu

* 2024 IEEE World Congress on Computational Intelligence (IEEE WCCI 2024)
30 June – 5 July 2024
Place: Yokohama, Japan
General Chairs: Akira Hirose and Hisao Ishibuchi
Editor Bing Xue
Victoria University of Wellington, New Zealand
Email: [email protected]

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